Update app.py

app.py

@@ -5,32 +5,32 @@ import numpy as np
 import os 
 from PIL import Image
 
-
 def perform(image):
-  """Perform the task of detection"""
-  # Predict with the model
-  results = model(image, save=True)  # predict on an image
-  # get the saved prediction
-  prediction_image = Image.open(os.path.join(results[0].save_dir, os.listdir(results[0].save_dir)[0]))
-  # initialize the output list to save the bbox
-  outputs = []
-  # Access the results
-  for result in results[0]:
-      xywh = result.boxes.xyxy[0].numpy().tolist()  # top-left-x, top-left-y, bottom-right-x, bottom-right-y
-      name = result.names[result.boxes.cls.item()] # classes
-      confs = float(result.boxes.conf)  # confidence score of each box
-      outputs.append({"xywh":xywh ,"conf":confs, "name":name})
-  # return the image and the bbox
-  return prediction_image, outputs
+    """Perform the task of detection"""
+    # Predict with the model
+    results = model(image, save=True)  # predict on an image
+    # get the saved prediction
+    prediction_image = Image.open(os.path.join(results[0].save_dir, os.listdir(results[0].save_dir)[0]))
+    # initialize the output list to save the bbox
+    outputs = []
+    # Access the results
+    for result in results[0]:
+        xywh = result.boxes.xyxy[0].numpy().tolist()  # top-left-x, top-left-y, bottom-right-x, bottom-right-y
+        name = result.names[result.boxes.cls.item()] # classes
+        confs = float(result.boxes.conf)  # confidence score of each box
+        outputs.append({"xywh":xywh ,"conf":confs, "name":name})
+    # return the image and the bbox
+    return prediction_image, outputs
 
-def load_model(model_name:str = "yolo11n.pt"):
-  """Model loading"""
-  try:
-    print(f"Loading the model {model_name}")
-    model = YOLO(model_name)
-  except Exception as e:
-    print(f"Error loading the model {e}")
-  return model
+def load_model(model_name: str = "yolo11n.pt"):
+    """Model loading"""
+    try:
+        print(f"Loading the model {model_name}")
+        model = YOLO(model_name)
+    except Exception as e:
+        print(f"Error loading the model {e}")
+        return None
+    return model
 
 # loading the model
 model = load_model()
@@ -47,12 +47,5 @@ demo = gr.Interface(
 
 # Launch the app
 if __name__ == "__main__":
-  username = os.environ.get('username')
-  password = os.environ.get('password')
-  print(username, " ",password)
-  demo.launch(share=True, 
-             ssr_mode=False,
-             server_name="0.0.0.0",
-             server_port=7860,
-             auth=(username, password)
-                )
+
+    demo.launch()